Zerank 1 Small
Compact 1.7B parameter model with novel ELO-based training on synthetic pairwise data for calibrated relevance scores. Half the cost of competing rerankers while maintaining strong ranking quality. If you want to compare the best rerankers for your data, try Agentset.
Model Information
- Provider
- ZeroEntropy
- License
- Open Source
- Price per 1M tokens
- $0.025
- Release Date
- 2025-07-10
- Model Name
- zerank-1-small
- Total Evaluations
- 3300
Performance Record
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Performance Overview
ELO ratings by dataset
Zerank 1 Small's ELO performance varies across different benchmark datasets, showing its strengths in specific domains.
Zerank 1 Small - ELO by Dataset
Detailed Metrics
Dataset breakdown
Performance metrics across different benchmark datasets, including accuracy and latency percentiles.
PG
Accuracy Metrics
- nDCG@5
- 0.000
- nDCG@10
- 0.000
- Recall@5
- 0.000
- Recall@10
- 0.000
Latency Distribution
- Mean
- 287ms
- P50 (Median)
- 274ms
- P90
- 345ms
DBPedia
Accuracy Metrics
- nDCG@5
- 0.000
- nDCG@10
- 0.000
- Recall@5
- 0.000
- Recall@10
- 0.000
Latency Distribution
- Mean
- 226ms
- P50 (Median)
- 223ms
- P90
- 241ms
business reports
Accuracy Metrics
- nDCG@5
- 0.000
- nDCG@10
- 0.000
- Recall@5
- 0.000
- Recall@10
- 0.000
Latency Distribution
- Mean
- 251ms
- P50 (Median)
- 242ms
- P90
- 298ms
MSMARCO
Accuracy Metrics
- nDCG@5
- 0.000
- nDCG@10
- 0.000
- Recall@5
- 0.000
- Recall@10
- 0.000
Latency Distribution
- Mean
- 217ms
- P50 (Median)
- 214ms
- P90
- 227ms
arguana
Accuracy Metrics
- nDCG@5
- 0.279
- nDCG@10
- 0.375
- Recall@5
- 0.520
- Recall@10
- 0.820
Latency Distribution
- Mean
- 256ms
- P50 (Median)
- 254ms
- P90
- 280ms
FiQa
Accuracy Metrics
- nDCG@5
- 0.114
- nDCG@10
- 0.124
- Recall@5
- 0.098
- Recall@10
- 0.125
Latency Distribution
- Mean
- 248ms
- P50 (Median)
- 244ms
- P90
- 266ms
Build RAG in Minutes, Not Months
Agentset gives you a complete RAG API with top-ranked rerankers and embedding models built in. Upload your data, call the API, and get accurate results from day one.
import { Agentset } from "agentset";
const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");
const results = await ns.search(
"What is multi-head attention?"
);
for (const result of results) {
console.log(result.text);
}Compare Models
See how it stacks up
Compare Zerank 1 Small with other top rerankers to understand the differences in performance, accuracy, and latency.